Paper Info
Title
Proximity and Priority: Applying a Gene Expression Algorithm to the Traveling Salesperson Problem
Abstract
In this paper we describe an environment for evolutionary computation that supports the movement of information from genome to phenotype with the possibility of one or more intermediate transformations. Our notion of a phenotype is more than a simple alternate representation of the binary genome. The construction of a phenotype is sufficiently different from the genome as to require its generation by a procedure that we call a gene expression algorithm. We discuss various reasons why benefits should accrue when combining gene expression algorithms with conventional genetic algorithms and illustrate these ideas with an algorithm to generate approximate solutions to the traveling salesperson problem. As in most genetic algorithms dealing with the TSP we run into the problem of an appropriate crossover operation for the strings that specify a permutation. To handle this issue we introduce a novel genome representation that admits a natural crossover operation and produces a permutation vector as an intermediate representation.
Year
DOI
Venue
2004
10.1016/j.parco.2003.12.017
Parallel Computing - Special issue: Parallel and nature-inspired computational paradigms and applications
Keywords
DocType
Volume
simple alternate representation,appropriate crossoveroperation,traveling salesperson problem,genetic algorithm,salesperson problem,gene expression algorithm,gene expression genetic algorithm,gene expression processing,novel genome representation,appropriate crossover operation,binary genome,evolutionary computation,intermediate transformation,gene expression strategy,conventional genetic algorithm,intermediate representation,permutation vector,fitness function,evolutionary computing,gene expression
Journal
30
Issue
ISSN
ISBN
5-6
1530-2075
0-7695-1926-1
Citations 
PageRank 
References 
3
0.60
4
Authors
1
Name
Order
Citations
PageRank
F. J. Burkowski125588.69